Literatura académica sobre el tema "RMSHE"
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Artículos de revistas sobre el tema "RMSHE"
S, Khamar Sabha, Usha H.N, Mithun B.N y Prathibha G.C. "Contrast enhancement using SHE, BHE, RMSHE and NOSHE with Entropy and EME". IJIREEICE 3, n.º 10 (15 de octubre de 2015): 29–32. http://dx.doi.org/10.17148/ijireeice.2015.31007.
Texto completoHashmi, Adeel, Abhinav Juneja, Naresh Kumar, Deepali Gupta, Hamza Turabieh, Grima Dhingra, Ravi Shankar Jha y Zelalem Kiros Bitsue. "Contrast Enhancement in Mammograms Using Convolution Neural Networks for Edge Computing Systems". Scientific Programming 2022 (11 de abril de 2022): 1–9. http://dx.doi.org/10.1155/2022/1882464.
Texto completoKUMI-BOATENG, Bernard y Yao Yevenyo ZIGGAH. "Empirical study on the integration of total least squares and radial basis function neural network for coordinate transformation". Ghana Journal of Science, Technology and Development 7, n.º 1 (8 de agosto de 2020): 38–57. http://dx.doi.org/10.47881/220.967x.
Texto completoKumi-Boateng, B. y Y. Y. Ziggah. "A 3D Procrustean Approach to Transform WGS84 Coordinates to Ghana War Office 1926 Reference Datum". Ghana Mining Journal 20, n.º 1 (7 de julio de 2020): 1–10. http://dx.doi.org/10.4314/gm.v20i1.1.
Texto completoAdekoya, Adebayo Felix, Isaac Kofi Nti y Benjamin Asubam Weyori. "Long Short-Term Memory Network for Predicting Exchange Rate of the Ghanaian Cedi". FinTech 1, n.º 1 (9 de diciembre de 2021): 25–43. http://dx.doi.org/10.3390/fintech1010002.
Texto completoChai, T. y R. R. Draxler. "Root mean square error (RMSE) or mean absolute error (MAE)? – Arguments against avoiding RMSE in the literature". Geoscientific Model Development 7, n.º 3 (30 de junio de 2014): 1247–50. http://dx.doi.org/10.5194/gmd-7-1247-2014.
Texto completoMentaschi, L., G. Besio, F. Cassola y A. Mazzino. "Problems in RMSE-based wave model validations". Ocean Modelling 72 (diciembre de 2013): 53–58. http://dx.doi.org/10.1016/j.ocemod.2013.08.003.
Texto completoHoe, Michael S., Christopher J. Dunn y Hailemariam Temesgen. "Multitemporal LiDAR improves estimates of fire severity in forested landscapes". International Journal of Wildland Fire 27, n.º 9 (2018): 581. http://dx.doi.org/10.1071/wf17141.
Texto completoLara-Cerecedo, Luis O., Jesús F. Hinojosa, Nun Pitalúa-Díaz, Yasuhiro Matsumoto y Alvaro González-Angeles. "Prediction of the Electricity Generation of a 60-kW Photovoltaic System with Intelligent Models ANFIS and Optimized ANFIS-PSO". Energies 16, n.º 16 (18 de agosto de 2023): 6050. http://dx.doi.org/10.3390/en16166050.
Texto completoLiu, Julin y Ken Chen. "Enterprise Financial Risk Prevention and Control and Data Analysis Method Based on Blockchain Technology". Mobile Information Systems 2022 (23 de junio de 2022): 1–7. http://dx.doi.org/10.1155/2022/9452342.
Texto completoTesis sobre el tema "RMSHE"
SAH, BIKASH KUMAR. "A NOVEL CONVOLUTIONAL NEURAL NETWORK FOR AIR POLLUTION FORECASTING". Thesis, DELHI TECHNOLOGICAL UNIVERSITY, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18792.
Texto completoChermiti, Amro. "Hur kan injicerad aktivitet individanpassas vid skelettscintigrafi? Effekten av patientspecifika parametrar". Thesis, Örebro universitet, Institutionen för hälsovetenskaper, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-84602.
Texto completoBackground: Bone scintigraphy is a nuclear medicine procedure. It is the most used nuclear diagnostic method and provides the opportunity to perform a full-body examination. For the method to retain its diagnostic quality, and to follow the recommendations of the Radiation Safety Authority, more knowledge is required on how the optimization should follow as low as reasonably achievable (ALARA). The purpose of the study was to optimize patient radiation dose and to investigate how the injected activity can be adapted to patient-specific parameters. Method: The study group consisted of 85 patients who underwent bone scintigraphy at the Central Hospital in Karlstad, from the period February-April 2020. Result: Showed that age and weight are patient-specific variables that should be considered when determining injected radiation dose. Conclusion: To optimize the examination for each patient, injected activity should be adjusted according to the patient’s body weight and age. More studies in where other parameters are investigated must be carried out.
Hast, Isak. "Quality Assessment of Spatial Data: Positional Uncertainties of the National Shoreline Data of Sweden". Thesis, Högskolan i Gävle, Avdelningen för Industriell utveckling, IT och Samhällsbyggnad, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-18743.
Texto completoAbdelhafeid, Faraj. "The Effect Upon Antenna Arrays of Variations of Element Orientation and Spacing in the Presence of Channel Noise, with an Application to Direction Finding". University of Dayton / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1525866099535246.
Texto completoCantarello, Luca. "Analisi delle previsioni meteorologiche mensili mediante il modello GLOBO (ISAC-CNR)". Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2014. http://amslaurea.unibo.it/7690/.
Texto completoMansour, Tony y Majdi Murtaja. "Applied estimation theory on power cable as transmission line". Thesis, Linnéuniversitetet, Institutionen för fysik och elektroteknik (IFE), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-46583.
Texto completoReigota, Nilvana dos Santos. "Comparação da transformada wavelet discreta e da transformada do cosseno, para compressão de imagens de impressão digital". Universidade de São Paulo, 2007. http://www.teses.usp.br/teses/disponiveis/18/18152/tde-27042007-101810/.
Texto completoThis research aims to compare the following fingerprint image compression methods: the discrete cosseno transform (DCT), Haar wavelet transform, Daubechies wavelets transform and wavelet scalar quantization (WSQ). The main interest is to find out the technique with the smallest distortion and higher compression ratio. Image quality is measured using peak signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR) and root mean square (ERMS). Image quality using these metrics showed best results for the DCT followed by WSQ, although the WSQ had the best compression time and presented the best quality when evaluated by the GrFinger 4.2 software.
Khurram, Jassal Muhammad. "The Effect of Optimization of Error Metrics". Thesis, Högskolan i Borås, Institutionen Handels- och IT-högskolan, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-20471.
Texto completoProgram: Magisterutbildning i informatik
Laskauskas, Ramūnas. "Vaizdo kontūrų nustatymo būdų analizė". Master's thesis, Lithuanian Academic Libraries Network (LABT), 2008. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2008~D_20080929_113638-76811.
Texto completoOne hundred various pictures with different size and number of elements were chosen for the method research of image outline evaluation. All these pictures were converted into grayscale pictures. Most of edge detection methods (filters) required to be blurred to reduce noise. Eight the most popular methods were chosen to evaluate the image outline: Canny, Sobel, Prewitt, Roberts, Zerocross, Laplacian, LoG, Marr-Hildreth. A Root Mean Square Error (RMSE) was computed for each edge picture with the best-chosen outline.
Morelli, Stefano. "Optimal pose selection for the calibration of an overconstrained Cable-Driven Parallel Robot". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022.
Buscar texto completoCapítulos de libros sobre el tema "RMSHE"
Mousania, Younes y Salman Karimi. "A Novel Improved Method of RMSHE-Based Technique for Mammography Images Enhancement". En Lecture Notes in Electrical Engineering, 31–42. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8672-4_3.
Texto completoBradai, Sonia, Carlo Trigona, Slim Naifar, Salvatore Baglio y Olfa Kanoun. "RMSHI Solutions for Electromagnetic Transducers from Environmental Vibration". En Lecture Notes in Electrical Engineering, 599–607. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04324-7_71.
Texto completoSu, Yong y Qingchuan Zhang. "Quality Assessment of Speckle Patterns by Estimating RMSE". En International Digital Imaging Correlation Society, 71–74. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51439-0_17.
Texto completoLi, Wang, Xiaoan Tang y Junda Zhang. "SRG and RMSE-Based Automated Segmentation for Volume Data". En Lecture Notes in Computer Science, 194–203. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71598-8_18.
Texto completoHaut, Nathan, Wolfgang Banzhaf y Bill Punch. "Correlation Versus RMSE Loss Functions in Symbolic Regression Tasks". En Genetic and Evolutionary Computation, 31–55. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8460-0_2.
Texto completoKo’adan, Mohammed A., Mohammed A. Bamatraf y Khalid Q. Shafal. "Clustering Analysis to Improve Web Search Ranking Using PCA and RMSE". En Advances on Smart and Soft Computing, 93–105. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6048-4_9.
Texto completoKobialka, Hans-Ulrich. "Friction estimation – optimization of sensor configuration with respect to RMSE and costs". En Proceedings, 741–55. Wiesbaden: Springer Fachmedien Wiesbaden, 2014. http://dx.doi.org/10.1007/978-3-658-05978-1_52.
Texto completoGong, Fengxun y Ma Yanqiu. "Analysis of Positioning Performance of the Algorithm of Time Sum of Arrival with RMSE". En Communications in Computer and Information Science, 579–91. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-7305-2_49.
Texto completoHan, Bo, Bo He, Mengmeng Ma, Tingting Sun, Tianhong Yan y Amaury Lendasse. "RMSE-ELM: Recursive Model Based Selective Ensemble of Extreme Learning Machines for Robustness Improvement". En Proceedings of ELM-2014 Volume 1, 273–92. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14063-6_24.
Texto completoChowdary, Nama Deepak, Tadepally Hrushikesh, Kusampudi Madhava Varma y Shaik Ali Basha. "Time Series Analysis and Forecast Accuracy Comparison of Models Using RMSE–Artificial Neural Networks". En Advances in Intelligent Systems and Computing, 317–25. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-0550-8_26.
Texto completoActas de conferencias sobre el tema "RMSHE"
Kuan, Sao-I., Jongmin Kim, Oh-Heum Kwon y Ha-Joo Song. "Canopy�K-means Combined Collaborative Filtering Using RMSE-minimization". En 2022 IEEE International Conference on Big Data and Smart Computing (BigComp). IEEE, 2022. http://dx.doi.org/10.1109/bigcomp54360.2022.00016.
Texto completoPatni, Hrithik, Akash Jagtap, Vaishali Bhoyar y Aditya Gupta. "Speech Emotion Recognition using MFCC, GFCC, Chromagram and RMSE features". En 2021 8th International Conference on Signal Processing and Integrated Networks (SPIN). IEEE, 2021. http://dx.doi.org/10.1109/spin52536.2021.9566046.
Texto completoFang, Qiang. "Is average RMSE appropriate for evaluating acoustic-to-articulatory inversion?" En 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). IEEE, 2019. http://dx.doi.org/10.1109/apsipaasc47483.2019.9023269.
Texto completoPinto, Breno, Varin Khera y Chun Che Fung. "Detecting security anomalies from internet traffic using the MA-RMSE algorithms". En 2009 7th IEEE International Conference on Industrial Informatics (INDIN). IEEE, 2009. http://dx.doi.org/10.1109/indin.2009.5195920.
Texto completoBradai, Sonia, Slim Naifar, Carlo Trigona, Salvatore Baglio y Olfa Kanoun. "Electromagnetic transducer with bistable-RMSHI for energy harvesting from very weak kinetic sources". En 2018 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). IEEE, 2018. http://dx.doi.org/10.1109/i2mtc.2018.8409784.
Texto completoMongia, Hukam C. "N+3 and N+4 Generation Aeropropulsion Engine Combustors: Part 3 — Small Engines’ Emissions and Axial Staging Combustion Technology". En ASME Turbo Expo 2013: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/gt2013-94572.
Texto completoSridhar, Bolli y Mohammed Zafar Ali Khan. "RMSE comparison of path loss models for UHF/VHF bands in India". En 2014 IEEE Region 10 Symposium. IEEE, 2014. http://dx.doi.org/10.1109/tenconspring.2014.6863052.
Texto completoIdiou, Nesrine, Fatah Benatia y Brahim Brahimi. "Bias And RMSE of Archimedean Copula using Moment And L-Moments Methods". En 2020 2nd International Conference on Mathematics and Information Technology (ICMIT). IEEE, 2020. http://dx.doi.org/10.1109/icmit47780.2020.9046998.
Texto completoLodetti, Paula Zenni, Edison A. C. Aranha Neto, Marcos A. Izumida Martins, Gabriel H. Dos S. Costa y Mathias Arno Ludwig. "MAE and RMSE Analysis of K-means Predictive Algorithm for Photovoltaic Generation". En 2022 International Conference on Electrical, Computer and Energy Technologies (ICECET). IEEE, 2022. http://dx.doi.org/10.1109/icecet55527.2022.9872976.
Texto completoShafin, Rubayet, Lingjia Liu y Jianzhong Zhang. "DoA Estimation and RMSE Characterization for 3D Massive-MIMO/FD-MIMO OFDM System". En GLOBECOM 2015 - 2015 IEEE Global Communications Conference. IEEE, 2014. http://dx.doi.org/10.1109/glocom.2014.7417413.
Texto completoInformes sobre el tema "RMSHE"
Brodie, Katherine, Brittany Bruder, Richard Slocum y Nicholas Spore. Simultaneous mapping of coastal topography and bathymetry from a lightweight multicamera UAS. Engineer Research and Development Center (U.S.), agosto de 2021. http://dx.doi.org/10.21079/11681/41440.
Texto completoErmolayev, Vadim, Frédéric Mallet, Vitaliy Yakovyna, Vyacheslav Kharchenko, Vitaliy Kobets, Artur Korniłowicz, Hennadiy Kravtsov, Mykola Nikitchenko, Сергій Олексійович Семеріков y Aleksander Spivakovsky, eds. ICTERI 2019: ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer : Proceedings of the 15th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer. Volume II: Workshops. Kherson, Ukraine, June 12-15, 2019. CEUR Workshop Proceedings, junio de 2019. http://dx.doi.org/10.31812/123456789/3170.
Texto completoPompeu, Gustavo y José Luiz Rossi. Real/Dollar Exchange Rate Prediction Combining Machine Learning and Fundamental Models. Inter-American Development Bank, septiembre de 2022. http://dx.doi.org/10.18235/0004491.
Texto completoPradhan, Nawa Raj. Estimating growing-season root zone soil moisture from vegetation index-based evapotranspiration fraction and soil properties in the Northwest Mountain region, USA. Engineer Research and Development Center (U.S.), septiembre de 2021. http://dx.doi.org/10.21079/11681/42128.
Texto completoPatwa, B., P. L. St-Charles, G. Bellefleur y B. Rousseau. Predictive models for first arrivals on seismic reflection data, Manitoba, New Brunswick, and Ontario. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/329758.
Texto completoConery, Ian, Brittany Bruder, Connor Geis, Jessamin Straub, Nicholas Spore y Katherine Brodie. Applicability of CoastSnap, a crowd-sourced coastal monitoring approach for US Army Corps of Engineers district use. Engineer Research and Development Center (U.S.), septiembre de 2023. http://dx.doi.org/10.21079/11681/47568.
Texto completoLetcher, Theodore, Julie Parno, Zoe Courville, Lauren Farnsworth y Jason Olivier. A generalized photon-tracking approach to simulate spectral snow albedo and transmittance using X-ray microtomography and geometric optics. Engineer Research and Development Center (U.S.), junio de 2023. http://dx.doi.org/10.21079/11681/47122.
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